class: center, middle, inverse, title-slide # SIVOCS --- <style> .center2 { margin: 0; position: absolute; top: 50%; left: 50%; -ms-transform: translate(-50%, -50%); transform: translate(-50%, -50%); } .large { font-size: 130% } .small { font-size: 70% } .remark-slide-content.hljs-default { border-top: 60px solid #23373B; } .remark-slide-content > h1 { font-size: 30px; margin-top: -75px; } </style> ## B1: How familiar are you with the concept of “social innovation” -- **H**: The familiarity with the concept of SI depends on the field of research. --- # B1 (NEW): Kruskal-Wallis test: SI familiarity depends on sci. domains? ``` ## ## Bartlett test of homogeneity of variances ## ## data: familiarWithSI.response. by domain ## Bartlett's K-squared = 12.931, df = 2, p-value = 0.001556 ``` ``` ## ## Kruskal-Wallis rank sum test ## ## data: familiarWithSI.response. by domain ## Kruskal-Wallis chi-squared = 45.694, df = 2, p-value = 1.196e-10 ``` * Mean ranks of the groups are not the same, SI fam. depends on domain --- # Pairwise Wilcoxon ``` ## ## Pairwise comparisons using Wilcoxon rank sum test with continuity correction ## ## data: data$familiarWithSI.response. and data$domain ## ## Biology and Medicine ## Humanities and Social Sciences 2.0e-09 ## Math., Natur. and Eng. Sci. 1 ## Humanities and Social Sciences ## Humanities and Social Sciences - ## Math., Natur. and Eng. Sci. 2.8e-07 ## ## P value adjustment method: bonferroni ``` --- # B1: *Familiarity with SI* across scientific domains <br> <img src="data:image/png;base64,#7780_int_meeting_files/figure-html/unnamed-chunk-4-1.svg" width="864" style="display: block; margin: auto;" /> <br> <br> * *Familiarity with SI* differs across scientific domains (Kruskal-Wallis p-value < 0.05) * *Biology and Medicine* and *Math., Natur, and Eng. Sci.* are **not** stat. significantly different (pairwise Wilcoxon p-value > 0.05) * *Humanities and Social Sciences* are significantly different than the others (pairwise t-test with each: p < 0.05) --- class:clear ## H: Generating deeper/better understanding of a specific social issue depends on (the level of) transdisciplinary involvement of citizens ``` ## ## Shapiro-Wilk normality test ## ## data: data.questions$Impactstatements.understanding. ## W = 0.55565, p-value < 2.2e-16 ``` ``` ## ## Shapiro-Wilk normality test ## ## data: data.questions$groupsInvolved.citiz. ## W = 0.5649, p-value < 2.2e-16 ``` --- ``` ## ## Kruskal-Wallis rank sum test ## ## data: Impactstatements.understanding. by groupsInvolved.citiz. ## Kruskal-Wallis chi-squared = 8.2846, df = 2, p-value = 0.01589 ``` * Different involvement levels make difference. --- ``` ## ## Spearman's rank correlation rho ## ## data: data.questions$Impactstatements.understanding. and data.questions$groupsInvolved.citiz. ## S = 5945746, p-value = 0.0041 ## alternative hypothesis: true rho is not equal to 0 ## sample estimates: ## rho ## 0.1535068 ``` ---
--- # D1: Motivation Types ## H: Motivation Types depend on sci. domains --- ###### Phenomenon .pull-left[ <img src="data:image/png;base64,#7780_int_meeting_files/figure-html/unnamed-chunk-10-1.svg" width="1152" /> ] .pull-right[ ``` ## ## Shapiro-Wilk normality test ## ## data: data.questions$motivation.pheno. ## W = 0.65462, p-value < 2.2e-16 ``` ``` ## ## Kruskal-Wallis rank sum test ## ## data: motivation.pheno. by domain ## Kruskal-Wallis chi-squared = 0.037102, df = 2, p-value = 0.9816 ``` * No stat. sig. difference between domains ] --- --- # Dim. Red.: PCA ``` ## [1] 0 ``` <img src="data:image/png;base64,#7780_int_meeting_files/figure-html/unnamed-chunk-13-1.svg" width="1152" /> --- # Dim. Red.: PCA <img src="data:image/png;base64,#7780_int_meeting_files/figure-html/unnamed-chunk-14-1.svg" width="1152" /> --- # Dim. Red.: PCA, imp. features in PC1 ``` ## groupsInvolved.citiz. targetGroupsGoals.empower. ## 0.2332093 0.2319459 ## impactTargetGroup.welfare. impactTargetGroup.socgr. ## 0.2288645 0.2283431 ## dissChannels.events. impactTargetGroup.pub. ## 0.2203846 0.2054193 ## benefitForNonAcademy targetGroupsGoals.diversity. ## 0.1970605 0.1938333 ## contribToSI.rate. groupsInvolved.media. ## 0.1887885 0.1885870 ``` --- # Dim. Red.: Factor Analysis <img src="data:image/png;base64,#7780_int_meeting_files/figure-html/unnamed-chunk-16-1.svg" width="1152" /> ``` ## Parallel analysis suggests that the number of factors = 10 and the number of components = NA ``` --- # Dim. Red.: FActor Analysis ``` ## Factor Analysis using method = minres ## Call: fa(r = data.num_questions, nfactors = 10, rotate = "oblimin", ## fm = "minres") ## Standardized loadings (pattern matrix) based upon correlation matrix ## MR2 MR1 MR7 MR3 MR6 MR9 MR5 MR4 ## transdisciplinaryExp.rate. -0.07 0.27 0.45 -0.05 -0.26 0.24 -0.01 0.13 ## familiarWithSI.response. -0.01 0.29 0.37 -0.14 0.12 0.02 -0.14 0.05 ## contribToSI.rate. 0.02 0.04 0.00 -0.03 0.10 0.89 0.01 -0.05 ## motivation.pheno. 0.00 0.08 -0.02 0.05 0.03 0.04 0.04 0.23 ## motivation.prob. -0.04 -0.02 0.05 -0.03 0.01 0.10 0.04 -0.13 ## motivation.welfare. 0.00 0.17 0.19 -0.02 0.02 0.34 -0.11 -0.54 ## benefitForNonAcademy -0.09 0.09 0.29 0.07 0.18 0.29 0.05 -0.38 ## groupsInvolved.res. -0.08 0.16 0.35 0.07 -0.16 0.10 -0.06 0.18 ## groupsInvolved.busi. -0.05 0.00 0.45 0.06 0.14 -0.18 0.02 -0.15 ## groupsInvolved.civsoc. 0.02 0.52 0.09 -0.14 0.35 -0.13 0.00 0.01 ## groupsInvolved.policy. -0.09 0.10 -0.11 0.01 0.77 0.01 -0.02 -0.01 ## groupsInvolved.citiz. -0.04 0.62 0.18 -0.01 0.08 -0.10 -0.01 0.07 ## groupsInvolved.media. 0.04 0.10 0.08 0.25 0.29 0.11 0.02 0.18 ## groupsInvolved.welfare. -0.04 0.50 0.02 -0.03 0.14 -0.01 0.09 -0.14 ## targetGroupsGoals.socneeds. -0.04 0.55 -0.05 -0.09 0.06 0.05 -0.06 -0.14 ## targetGroupsGoals.socgroups. -0.02 0.71 -0.21 0.01 -0.11 0.15 -0.07 0.04 ## targetGroupsGoals.improve. 0.14 0.23 0.07 0.00 -0.08 -0.04 -0.18 -0.29 ## targetGroupsGoals.empower. 0.06 0.44 0.02 0.05 0.21 0.09 -0.12 0.06 ## targetGroupsGoals.diversity. -0.01 0.33 0.06 0.11 0.20 0.02 0.05 0.44 ## concepts.pub. -0.03 -0.01 -0.04 0.42 0.00 -0.11 0.08 -0.09 ## concepts.data. 0.02 -0.15 -0.03 0.59 -0.02 -0.10 -0.12 0.03 ## concepts.code. 0.01 -0.03 0.09 0.47 -0.10 -0.18 -0.02 -0.03 ## concepts.infra. 0.05 -0.03 0.10 0.29 0.00 -0.09 0.00 0.06 ## concepts.review. 0.01 -0.12 0.24 0.04 0.10 0.04 0.03 0.29 ## impactTargetGroup.pub. -0.04 0.02 0.55 0.14 0.06 0.29 -0.02 -0.14 ## impactTargetGroup.busi. 0.01 -0.10 0.71 0.07 0.05 -0.12 -0.02 -0.08 ## impactTargetGroup.socgr. -0.01 0.65 0.06 0.10 0.07 0.10 -0.02 -0.05 ## impactTargetGroup.welfare. 0.00 0.32 0.24 0.00 0.14 0.18 0.14 -0.07 ## impactTargetGroup.civsoc. 0.04 0.29 0.18 -0.04 0.32 0.12 -0.13 0.07 ## impactTargetGroup.policy. 0.01 -0.07 0.24 -0.08 0.61 0.26 -0.14 0.06 ## impactTargetGroup.acad. 0.08 -0.11 0.35 0.09 -0.05 0.12 -0.04 0.26 ## adoptByPolicy.rate. 0.55 0.01 0.12 -0.08 0.04 -0.15 0.19 0.04 ## Impactstatements.capab. 0.81 -0.04 -0.09 0.06 -0.03 0.05 -0.02 0.01 ## Impactstatements.emanc. 0.89 -0.06 0.02 0.01 0.00 -0.02 0.05 -0.02 ## Impactstatements.understanding. 0.92 0.03 0.00 0.01 0.00 0.00 -0.01 -0.03 ## Impactstatements.mitig. 0.88 0.07 0.04 -0.01 0.00 0.03 0.10 0.03 ## Impactstatements.unknown. 0.83 0.01 0.00 -0.04 0.02 -0.01 -0.06 0.01 ## Impactstatements.unaddressed. 0.46 0.01 -0.11 -0.03 -0.07 0.28 -0.09 -0.01 ## dissChannels.peer. 0.13 -0.06 -0.06 0.13 0.08 -0.04 -0.09 -0.02 ## dissChannels.mono. -0.10 0.14 -0.02 -0.04 0.09 0.28 0.09 0.38 ## dissChannels.conf. 0.04 0.14 0.00 -0.01 -0.02 -0.13 -0.11 0.05 ## dissChannels.policy. 0.05 0.03 0.01 0.07 0.48 -0.01 -0.09 -0.01 ## dissChannels.trad. 0.00 0.01 -0.01 0.46 0.20 0.19 0.00 0.14 ## dissChannels.prof. -0.06 0.14 0.05 0.19 0.10 0.33 0.13 0.10 ## dissChannels.web. -0.10 0.12 0.02 0.44 -0.04 0.01 0.12 -0.07 ## dissChannels.socmed. -0.03 0.01 0.15 0.38 0.05 0.07 0.07 -0.05 ## dissChannels.platf. 0.08 0.15 0.06 0.48 -0.09 -0.05 -0.09 0.00 ## dissChannels.consult. -0.05 0.14 0.17 0.21 0.03 0.09 -0.06 0.06 ## dissChannels.events. -0.08 0.40 0.03 0.15 0.17 0.16 0.11 -0.03 ## dissChannels.public. 0.03 0.10 0.06 0.36 0.00 0.23 0.17 0.02 ## scalabilityRating.up. -0.08 0.04 0.02 -0.03 0.01 0.06 0.71 0.08 ## scalabilityRating.out. 0.12 -0.02 -0.05 -0.02 -0.05 0.04 0.81 -0.01 ## scalabilityRating.deep. 0.17 -0.06 0.04 0.04 -0.04 -0.12 0.62 -0.07 ## MR10 MR8 h2 u2 com ## transdisciplinaryExp.rate. -0.04 0.02 0.42 0.579 3.3 ## familiarWithSI.response. -0.02 0.07 0.40 0.596 3.0 ## contribToSI.rate. 0.16 0.02 1.00 -0.002 1.1 ## motivation.pheno. 0.65 -0.08 0.49 0.509 1.3 ## motivation.prob. 0.76 0.04 0.67 0.327 1.1 ## motivation.welfare. 0.12 0.05 0.74 0.257 2.5 ## benefitForNonAcademy -0.09 0.04 0.57 0.428 3.9 ## groupsInvolved.res. 0.01 0.25 0.33 0.667 4.1 ## groupsInvolved.busi. 0.05 0.04 0.29 0.711 1.9 ## groupsInvolved.civsoc. 0.02 -0.19 0.54 0.458 2.5 ## groupsInvolved.policy. 0.06 0.02 0.67 0.331 1.1 ## groupsInvolved.citiz. -0.02 0.09 0.51 0.494 1.3 ## groupsInvolved.media. -0.07 0.21 0.36 0.643 4.6 ## groupsInvolved.welfare. -0.02 0.22 0.42 0.576 1.8 ## targetGroupsGoals.socneeds. -0.02 0.15 0.43 0.569 1.5 ## targetGroupsGoals.socgroups. 0.09 0.04 0.56 0.441 1.4 ## targetGroupsGoals.improve. 0.12 0.29 0.31 0.686 4.8 ## targetGroupsGoals.empower. 0.08 0.05 0.42 0.582 2.0 ## targetGroupsGoals.diversity. 0.05 0.01 0.45 0.545 2.6 ## concepts.pub. 0.09 0.14 0.22 0.777 1.7 ## concepts.data. 0.07 0.08 0.41 0.587 1.4 ## concepts.code. -0.03 -0.08 0.28 0.721 1.6 ## concepts.infra. 0.00 0.19 0.16 0.842 2.4 ## concepts.review. 0.02 0.21 0.20 0.796 3.7 ## impactTargetGroup.pub. -0.06 0.06 0.65 0.346 1.9 ## impactTargetGroup.busi. 0.11 -0.03 0.53 0.469 1.2 ## impactTargetGroup.socgr. 0.00 -0.12 0.58 0.421 1.2 ## impactTargetGroup.welfare. -0.09 0.16 0.45 0.551 4.4 ## impactTargetGroup.civsoc. -0.01 -0.20 0.47 0.534 4.3 ## impactTargetGroup.policy. 0.02 -0.02 0.72 0.285 1.9 ## impactTargetGroup.acad. 0.13 0.12 0.25 0.746 3.5 ## adoptByPolicy.rate. 0.07 0.00 0.42 0.575 1.6 ## Impactstatements.capab. 0.02 0.00 0.69 0.311 1.1 ## Impactstatements.emanc. 0.01 0.02 0.85 0.155 1.0 ## Impactstatements.understanding. -0.01 0.01 0.83 0.173 1.0 ## Impactstatements.mitig. -0.02 -0.01 0.81 0.187 1.0 ## Impactstatements.unknown. -0.03 0.00 0.66 0.341 1.0 ## Impactstatements.unaddressed. -0.11 -0.12 0.27 0.728 2.3 ## dissChannels.peer. 0.03 0.28 0.12 0.883 2.8 ## dissChannels.mono. -0.14 0.14 0.35 0.651 3.4 ## dissChannels.conf. -0.02 0.41 0.20 0.805 1.7 ## dissChannels.policy. 0.01 0.08 0.27 0.734 1.2 ## dissChannels.trad. -0.07 0.09 0.36 0.641 2.1 ## dissChannels.prof. 0.04 0.19 0.37 0.629 4.0 ## dissChannels.web. -0.06 0.00 0.23 0.770 1.6 ## dissChannels.socmed. 0.03 -0.16 0.23 0.772 2.0 ## dissChannels.platf. 0.04 -0.32 0.34 0.659 2.3 ## dissChannels.consult. 0.02 -0.09 0.17 0.830 4.3 ## dissChannels.events. 0.01 0.03 0.40 0.598 2.5 ## dissChannels.public. -0.15 0.01 0.27 0.731 3.0 ## scalabilityRating.up. -0.07 -0.11 0.51 0.490 1.1 ## scalabilityRating.out. 0.08 0.06 0.77 0.232 1.1 ## scalabilityRating.deep. 0.06 -0.01 0.53 0.472 1.3 ## ## MR2 MR1 MR7 MR3 MR6 MR9 MR5 MR4 MR10 MR8 ## SS loadings 4.53 4.00 2.64 2.17 2.53 2.49 2.01 1.38 1.28 1.12 ## Proportion Var 0.09 0.08 0.05 0.04 0.05 0.05 0.04 0.03 0.02 0.02 ## Cumulative Var 0.09 0.16 0.21 0.25 0.30 0.35 0.38 0.41 0.43 0.46 ## Proportion Explained 0.19 0.17 0.11 0.09 0.10 0.10 0.08 0.06 0.05 0.05 ## Cumulative Proportion 0.19 0.35 0.46 0.55 0.66 0.76 0.84 0.90 0.95 1.00 ## ## With factor correlations of ## MR2 MR1 MR7 MR3 MR6 MR9 MR5 MR4 MR10 MR8 ## MR2 1.00 -0.12 -0.07 0.02 -0.14 -0.06 0.30 -0.02 0.05 -0.03 ## MR1 -0.12 1.00 0.25 0.02 0.39 0.41 -0.09 0.01 0.06 0.12 ## MR7 -0.07 0.25 1.00 0.19 0.29 0.29 -0.07 -0.12 0.07 0.14 ## MR3 0.02 0.02 0.19 1.00 0.01 0.06 0.01 0.07 0.04 0.09 ## MR6 -0.14 0.39 0.29 0.01 1.00 0.32 -0.14 0.03 0.11 0.03 ## MR9 -0.06 0.41 0.29 0.06 0.32 1.00 -0.03 -0.09 0.21 0.17 ## MR5 0.30 -0.09 -0.07 0.01 -0.14 -0.03 1.00 0.12 0.04 0.00 ## MR4 -0.02 0.01 -0.12 0.07 0.03 -0.09 0.12 1.00 -0.11 -0.05 ## MR10 0.05 0.06 0.07 0.04 0.11 0.21 0.04 -0.11 1.00 0.05 ## MR8 -0.03 0.12 0.14 0.09 0.03 0.17 0.00 -0.05 0.05 1.00 ## ## Mean item complexity = 2.2 ## Test of the hypothesis that 10 factors are sufficient. ## ## The degrees of freedom for the null model are 1378 and the objective function was 46.29 with Chi Square of 15808.71 ## The degrees of freedom for the model are 893 and the objective function was 26.19 ## ## The root mean square of the residuals (RMSR) is 0.03 ## The df corrected root mean square of the residuals is 0.04 ## ## The harmonic number of observations is 274 with the empirical chi square 911.36 with prob < 0.33 ## The total number of observations was 361 with Likelihood Chi Square = 8770.49 with prob < 0 ## ## Tucker Lewis Index of factoring reliability = 0.139 ## RMSEA index = 0.156 and the 90 % confidence intervals are 0.154 0.16 ## BIC = 3511.73 ## Fit based upon off diagonal values = 0.97 ``` --- ``` ## lavaan 0.6-9 did NOT end normally after 2345 iterations ## ** WARNING ** Estimates below are most likely unreliable ## ## Estimator ML ## Optimization method NLMINB ## Number of model parameters 112 ## ## Used Total ## Number of observations 56 361 ## ## Model Test User Model: ## ## Test statistic NA ## Degrees of freedom NA ## ## Parameter Estimates: ## ## Standard errors Standard ## Information Expected ## Information saturated (h1) model Structured ## ## Latent Variables: ## Estimate Std.Err z-value P(>|z|) Std.lv Std.all ## F1 =~ ## grpsInvlvd.cv. 1.000 0.330 0.484 ## grpsInvlvd.ct. 1.833 NA 0.605 0.733 ## grpsInvlvd.wl. 1.412 NA 0.466 0.567 ## trgtGrpsGls.s. 0.958 NA 0.316 0.633 ## trgtGrpsGls.s. 0.839 NA 0.277 0.567 ## trgtGrpsGls.m. 0.890 NA 0.294 0.629 ## F2 =~ ## adptByPlcy.rt. 1.000 11.262 0.455 ## Impctsttmnts.. 2.266 NA 25.522 0.882 ## Impctsttmnts.. 2.258 NA 25.433 0.863 ## Impctsttmnts.. 1.984 NA 22.347 0.724 ## Impctsttmnts.. 1.977 NA 22.267 0.671 ## Impctsttmnts.. 1.053 NA 11.855 0.558 ## Impctsttmnts.. 0.417 NA 4.700 0.272 ## F3 =~ ## concepts.pub. 1.000 0.073 0.257 ## concepts.data. 3.670 NA 0.269 0.543 ## concepts.code. 4.604 NA 0.337 0.722 ## concepts.infr. 3.740 NA 0.274 0.596 ## dssChnnls.trd. 1.900 NA 0.139 0.279 ## dissChnnls.wb. 1.459 NA 0.107 0.291 ## dssChnnls.plt. 3.698 NA 0.271 0.589 ## F4 =~ ## trgtGrpsGls.d. 1.000 0.460 1.000 ## F5 =~ ## sclbltyRtng.p. 1.000 21.490 0.674 ## sclbltyRtng.t. 1.442 NA 30.978 0.847 ## sclbltyRtng.d. 1.105 NA 23.744 0.610 ## F6 =~ ## grpsInvlvd.pl. 1.000 0.508 0.657 ## impctTrgtGrp.. 6.214 NA 3.154 0.940 ## dssChnnls.plc. 0.406 NA 0.206 0.475 ## F7 =~ ## trnsdscplnrE.. 1.000 0.071 0.037 ## grpsInvlvd.bs. 6.390 NA 0.457 0.607 ## impctTrgtGrp.. 20.391 NA 1.457 0.530 ## impctTrgtGrp.. 38.209 NA 2.731 0.798 ## F8 =~ ## dssChnnls.cnf. 1.000 0.225 1.000 ## F9 =~ ## contribTSI.rt. 1.000 2.348 1.000 ## F10 =~ ## motivatin.phn. 1.000 NA NA ## motivatin.prb. -0.004 NA NA NA ## ## Covariances: ## Estimate Std.Err z-value P(>|z|) Std.lv Std.all ## F1 ~~ ## F2 -1.057 NA -0.284 -0.284 ## F3 -0.002 NA -0.085 -0.085 ## F4 0.093 NA 0.611 0.611 ## F5 -2.118 NA -0.299 -0.299 ## F6 0.068 NA 0.409 0.409 ## F7 0.004 NA 0.167 0.167 ## F8 0.011 NA 0.153 0.153 ## F9 0.350 NA 0.452 0.452 ## F10 0.263 NA 0.092 0.092 ## F2 ~~ ## F3 0.207 NA 0.251 0.251 ## F4 -0.772 NA -0.149 -0.149 ## F5 93.842 NA 0.388 0.388 ## F6 -0.265 NA -0.046 -0.046 ## F7 -0.031 NA -0.038 -0.038 ## F8 -0.527 NA -0.208 -0.208 ## F9 7.343 NA 0.278 0.278 ## F10 1.885 NA 0.019 0.019 ## F3 ~~ ## F4 0.005 NA 0.162 0.162 ## F5 -0.097 NA -0.062 -0.062 ## F6 -0.004 NA -0.114 -0.114 ## F7 0.003 NA 0.505 0.505 ## F8 -0.001 NA -0.059 -0.059 ## F9 -0.023 NA -0.136 -0.136 ## F10 -0.003 NA -0.005 -0.005 ## F4 ~~ ## F5 -2.603 NA -0.263 -0.263 ## F6 0.077 NA 0.330 0.330 ## F7 0.001 NA 0.031 0.031 ## F8 0.002 NA 0.015 0.015 ## F9 0.126 NA 0.117 0.117 ## F10 0.263 NA 0.066 0.066 ## F5 ~~ ## F6 -1.838 NA -0.168 -0.168 ## F7 0.114 NA 0.074 0.074 ## F8 -0.582 NA -0.120 -0.120 ## F9 -1.059 NA -0.021 -0.021 ## F10 -5.495 NA -0.030 -0.030 ## F6 ~~ ## F7 0.009 NA 0.250 0.250 ## F8 -0.035 NA -0.304 -0.304 ## F9 0.485 NA 0.406 0.406 ## F10 0.318 NA 0.073 0.073 ## F7 ~~ ## F8 -0.002 NA -0.122 -0.122 ## F9 -0.010 NA -0.058 -0.058 ## F10 0.025 NA 0.040 0.040 ## F8 ~~ ## F9 -0.034 NA -0.065 -0.065 ## F10 -0.047 NA -0.024 -0.024 ## F9 ~~ ## F10 0.954 NA 0.047 0.047 ## ## Variances: ## Estimate Std.Err z-value P(>|z|) Std.lv Std.all ## .grpsInvlvd.cv. 0.355 NA 0.355 0.765 ## .grpsInvlvd.ct. 0.315 NA 0.315 0.462 ## .grpsInvlvd.wl. 0.459 NA 0.459 0.679 ## .trgtGrpsGls.s. 0.150 NA 0.150 0.600 ## .trgtGrpsGls.s. 0.162 NA 0.162 0.678 ## .trgtGrpsGls.m. 0.132 NA 0.132 0.604 ## .adptByPlcy.rt. 486.887 NA 486.887 0.793 ## .Impctsttmnts.. 186.762 NA 186.762 0.223 ## .Impctsttmnts.. 222.671 NA 222.671 0.256 ## .Impctsttmnts.. 453.456 NA 453.456 0.476 ## .Impctsttmnts.. 604.248 NA 604.248 0.549 ## .Impctsttmnts.. 310.552 NA 310.552 0.688 ## .Impctsttmnts.. 276.251 NA 276.251 0.926 ## .concepts.pub. 0.076 NA 0.076 0.934 ## .concepts.data. 0.173 NA 0.173 0.705 ## .concepts.code. 0.104 NA 0.104 0.479 ## .concepts.infr. 0.136 NA 0.136 0.645 ## .dssChnnls.trd. 0.230 NA 0.230 0.922 ## .dissChnnls.wb. 0.123 NA 0.123 0.915 ## .dssChnnls.plt. 0.138 NA 0.138 0.653 ## .trgtGrpsGls.d. 0.000 0.000 0.000 ## .sclbltyRtng.p. 554.390 NA 554.390 0.546 ## .sclbltyRtng.t. 377.105 NA 377.105 0.282 ## .sclbltyRtng.d. 950.079 NA 950.079 0.628 ## .grpsInvlvd.pl. 0.339 NA 0.339 0.568 ## .impctTrgtGrp.. 1.305 NA 1.305 0.116 ## .dssChnnls.plc. 0.145 NA 0.145 0.774 ## .trnsdscplnrE.. 3.729 NA 3.729 0.999 ## .grpsInvlvd.bs. 0.358 NA 0.358 0.632 ## .impctTrgtGrp.. 5.438 NA 5.438 0.719 ## .impctTrgtGrp.. 4.251 NA 4.251 0.363 ## .dssChnnls.cnf. 0.000 0.000 0.000 ## .contribTSI.rt. 0.000 0.000 0.000 ## .motivatin.phn. 78.316 NA 78.316 21.450 ## .motivatin.prb. 4.386 NA 4.386 1.000 ## F1 0.109 NA 1.000 1.000 ## F2 126.837 NA 1.000 1.000 ## F3 0.005 NA 1.000 1.000 ## F4 0.211 NA 1.000 1.000 ## F5 461.800 NA 1.000 1.000 ## F6 0.258 NA 1.000 1.000 ## F7 0.005 NA 1.000 1.000 ## F8 0.051 NA 1.000 1.000 ## F9 5.515 NA 1.000 1.000 ## F10 -74.665 NA NA NA ```